Explore This Laboratory

About the Lab

The Massachusetts General Hospital Surgical Artificial Intelligence and Innovation Laboratory (SAIIL) is a multidisciplinary group composed of surgeons, engineers and data scientists who are passionate about redesigning the delivery of surgical care. The team is made up of surgeons in Mass General’s Department of Surgery and scientists from Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory (CSAIL). Together, our team has developed tools to help unlock the intraoperative phase of care.

Our primary emphasis is on utilizing computer vision to investigate the intraoperative phase of care through real-time, automated surgical analysis. In other words, we use artificial intelligence (AI) to automatically analyze and interpret videos of operations as they are occurring. The goal is to teach the AI to understand what is happening in an operation, determine whether the risk for a postoperative complication is high, or even provide surgeons with additional data to improve operating room decisions.

While the field of surgical research has improved its ability to study pre- and postoperative events and risk using claims data and patient registries, the intraoperative phase of care remains difficult to study.

In a review of nationwide data, researchers estimated that major intraoperative adverse events (i.e. accidental damage to bowel or major blood vessels) can occur in 2% of all operations. Approximately 22 million general surgery operations are performed each year in the United States and 440,000 patients may experience an intraoperative adverse event a year. The cost of hospital admission is 41% higher in these patients, and the consequences of adverse events can impact their quality of life. An expected one-day stay could turn into a month-long hospitalization, additional procedures, prolonged rehabilitation, or a host of other life-altering consequences.

Research Vision and Goals

We will help big data realize personalized medicine for surgical patients. We envision a technology-enabled operating room that pulls data from prior operations for real-time clinical decision making, much like a GPS for surgeons.

We are building technology as the foundation for a worldwide database of surgical cases. A surgeon learns and improves one operation at a time. An AI system can learn from thousands of cases simultaneously. It allows for the collection, analysis and sharing of quantitative evidence in real-time across multiple surgeons—a “collective surgical consciousness.”

The goals of our research in surgery are to:

  • Democratize surgical knowledge
  • Lower costs
  • Improve outcomes
  • Reduce morbidity and mortality

Research Projects

Our research focuses on using computer analysis to improve operations. By using artificial intelligence, we can work to improve surgical care.

Artificial Intelligence for Risk Prediction from Intraoperative Events

This study will utilize our team's previously developed computer vision-based analysis of intraoperative video to integrate quantitative intraoperative data with peri-operative data to improve the prediction of patient-specific complications and readmissions for patients undergoing laparoscopic cholecystectomy.

Funding: CRICO Risk Management Foundation

Automated Intraoperative POEM Analysis: A Machine Learning Approach

The goal of this study is to develop artificial intelligence to generate compact segmentation and summarization of an endoscopic surgical procedure (per oral endoscopy myotomy) in real-time. This study builds off our initial pilot approach utilizing support vector machines for visual classification in sleeve gastrectomy and pivots to the use of deep learning for our visual model.

Funding: Natural Orifice Surgery Consortium for Assessment and Research

News

Utilizing Computer Vision to Investigate the Intraoperative Phase of Care through Real-Time, Automated Surgical Analysis
Intelligent Health Summit; Basel, Switzerland; September 2019
A presentation by Mass General surgeon Ozanan Meireles, MD

Artificial Intelligence in Surgery
European Association of Endoscopic Surgeons; Seville, Spain; June 2019
A keynote address given by Daniel Hashimoto, MD, MS

How will Artificial Intelligence Impact Surgical Patient Care? Part 2
OR Manager, May 2019

How will Artificial Intelligence Impact Surgical Patient Care? Part 1
OR Manager, April 2019

Young Alumni Service Award
UPenn Alumni, April 2019
Daniel Hashimoto, MD, MS, awarded Young Alumni Service Award from the University of Pennsylvania School of Medicine for contributions to the field of surgery in artificial intelligence as well as for service to the Penn Medicine alumni community.

Surgeons Seek Consensus on Bile Duct Injury Prevention
General Surgery News, January 2019

Season 2, Episode 3
EY Better Innovations podcast, January 2019
Mass General SAIIL Fellow Dan Hashimoto, MD, participates in a roundtable discussion on the use of artifical intelligence to analyze operative data

To Boldly Go - Remote
Harvard Medicine Magazine, January 2019
Mass General SAIIL Fellow Dan Hashimoto, MD, discusses the intersection of artificial intelligence and virtual reality to train surgeons

The Robots Are Coming. Will They Work With Us?
PBS News, December 2018
Mass General surgeon Ozanan Meireles, MD, and SAIIL Fellow Dan Hashimoto, MD, discuss their work developing artificial intelligence for use in the operating room

Using Video Data for Safer Surgery
TEDx, August 2018
Mass General SAIIL Fellow Dan Hashimoto, MD, gave a TEDx Talk on using artificial intelligence in surgery to create the “collective surgical consciousness”

Surgical Fingerprints: Real-Time Analysis and Summarization of Intraoperative Events
World Medical Innovation Forum, April 2018
Mass General SAIIL Fellow Dan Hashimoto, MD, presents the lab's work on artificial intelligence at the World Medical Innovation Forum

Shrinking Data for Surgical Training
MIT News, June 2017
Mass General and MIT Innovators

2017 40 Under 40 Healthcare Innovators
MedTech Boston, April 2017
Mass General SAIIL Fellow Dan Hashimoto, MD, named one of MedTech Boston’s "40 under 40 Healthcare Innovators"

Publications

The following are publications from the Mass General SAIIL team:

Meet the Team

Director

Ozanan Meireles, MD, FACS
General Surgeon, Mass General
Assistant Professor of Surgery, Harvard Medical School

Research Team

Daniel A. Hashimoto, MD, MS
Associate Director of Research

Yutong Ban, PhD
Postdoctoral Research Fellow

Allison Navarrete-Welton
Research Assistant

Guy Rosman, PhD
Associate Director of Engineering

Caitlin Stafford, CCRP
Research Specialist

Thomas M. Ward, MD
Surgical AI & Innovation Fellow

Ula Widocki
Graduate Student

Elan Witkowski, MD, MPH
General Surgeon, Mass General
Instructor of Surgery, Harvard Medical School

Key Collaborators

Teodor Grantcharov, MD, PhD
Professor of Surgery, University of Toronto
Director, International Centre for Surgical Safety

Quanzeng Li, PhD
Associate Professor of Radiology

Daniela Rus, PhD
Director, Computer Science and Artificial Intelligence Laboratory, MIT